stim lfp response

actions/stimulus-lfp-response/attributes.yaml

@@ -1,5 +1,5 @@
 registered: '2019-10-14T17:03:05'
 data:
   results: results.csv
-  notebook: 10-calculate-stimulus-lfp-response.ipynb
+  notebook: 20_stimulus-lfp-response.ipynb
-  html: 10-calculate-stimulus-lfp-response.html
+  html: 20_stimulus-lfp-response.html

actions/stimulus-lfp-response/data/10-calculate-stimulus-lfp-response.html

@@ -13171,7 +13171,7 @@ div#notebook {
 
 
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-<pre>15:15:05 [I] klustakwik KlustaKwik2 version 0.2.6
+<pre>10:26:07 [I] klustakwik KlustaKwik2 version 0.2.6
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+<span class="p">(</span><span class="n">output</span> <span class="o">/</span> <span class="s1">&#39;data&#39;</span><span class="p">)</span><span class="o">.</span><span class="n">mkdir</span><span class="p">(</span><span class="n">parents</span><span class="o">=</span><span class="kc">True</span><span class="p">,</span> <span class="n">exist_ok</span><span class="o">=</span><span class="kc">True</span><span class="p">)</span>
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 <div class=" highlight hl-ipython3"><pre><span></span><span class="k">def</span> <span class="nf">get_lim</span><span class="p">(</span><span class="n">action_id</span><span class="p">):</span>
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 <div class=" highlight hl-ipython3"><pre><span></span><span class="k">def</span> <span class="nf">signaltonoise</span><span class="p">(</span><span class="n">a</span><span class="p">,</span> <span class="n">axis</span><span class="o">=</span><span class="mi">0</span><span class="p">,</span> <span class="n">ddof</span><span class="o">=</span><span class="mi">0</span><span class="p">):</span>
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 <div class=" highlight hl-ipython3"><pre><span></span><span class="k">def</span> <span class="nf">compute_energy</span><span class="p">(</span><span class="n">p</span><span class="p">,</span> <span class="n">f</span><span class="p">,</span> <span class="n">f1</span><span class="p">,</span> <span class="n">f2</span><span class="p">):</span>
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 <div class=" highlight hl-ipython3"><pre><span></span><span class="k">def</span> <span class="nf">find_theta_peak</span><span class="p">(</span><span class="n">p</span><span class="p">,</span> <span class="n">f</span><span class="p">):</span>
@@ -13350,7 +13350,7 @@ div#notebook {
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 <div class=" highlight hl-ipython3"><pre><span></span><span class="k">def</span> <span class="nf">compute_half_width</span><span class="p">(</span><span class="n">p</span><span class="p">,</span> <span class="n">f</span><span class="p">,</span> <span class="n">m_p</span><span class="p">,</span> <span class="n">m_f</span><span class="p">):</span>
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 <div class=" highlight hl-ipython3"><pre><span></span><span class="k">def</span> <span class="nf">compute_stim_peak</span><span class="p">(</span><span class="n">p</span><span class="p">,</span> <span class="n">f</span><span class="p">,</span> <span class="n">s_f</span><span class="p">):</span>
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 <div class=" highlight hl-ipython3"><pre><span></span><span class="n">NFFT</span> <span class="o">=</span> <span class="mi">10000</span>
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 <div class=" highlight hl-ipython3"><pre><span></span><span class="k">def</span> <span class="nf">process</span><span class="p">(</span><span class="n">row</span><span class="p">):</span>
@@ -13486,7 +13486,7 @@ div#notebook {
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 <div class=" highlight hl-ipython3"><pre><span></span><span class="n">results</span> <span class="o">=</span> <span class="n">channel_groups</span><span class="o">.</span><span class="n">merge</span><span class="p">(</span>
@@ -13512,18 +13512,138 @@ div#notebook {
 
  
  
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+<div class="output_area">
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+    <div class="prompt"></div>
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+<div class="output_subarea output_stream output_stdout output_text">
+<pre>
+</pre>
+</div>
+</div>
+
+</div>
+</div>
+
+</div>
+<div class="cell border-box-sizing code_cell rendered">
+<div class="input">
+<div class="prompt input_prompt">In&nbsp;[17]:</div>
+<div class="inner_cell">
+    <div class="input_area">
+<div class=" highlight hl-ipython3"><pre><span></span><span class="n">psd</span><span class="p">,</span> <span class="n">freqs</span> <span class="o">=</span> <span class="p">{},</span> <span class="p">{}</span>
+<span class="k">for</span> <span class="n">i</span><span class="p">,</span> <span class="n">row</span> <span class="ow">in</span> <span class="n">tqdm</span><span class="p">(</span><span class="n">channel_groups</span><span class="o">.</span><span class="n">iterrows</span><span class="p">(),</span> <span class="n">total</span><span class="o">=</span><span class="nb">len</span><span class="p">(</span><span class="n">channel_groups</span><span class="p">)):</span>
+    <span class="n">action_id</span> <span class="o">=</span> <span class="n">row</span><span class="p">[</span><span class="s1">&#39;action&#39;</span><span class="p">]</span>
+    <span class="n">channel_group</span> <span class="o">=</span> <span class="n">row</span><span class="p">[</span><span class="s1">&#39;channel_group&#39;</span><span class="p">]</span>
+    <span class="n">action_group</span> <span class="o">=</span> <span class="n">f</span><span class="s1">&#39;</span><span class="si">{action_id}</span><span class="s1">_</span><span class="si">{channel_group}</span><span class="s1">&#39;</span>
+    <span class="n">lfp</span> <span class="o">=</span> <span class="n">data_loader</span><span class="o">.</span><span class="n">lfp</span><span class="p">(</span><span class="n">action_id</span><span class="p">,</span> <span class="n">channel_group</span><span class="p">)</span>
+    <span class="n">clean_lfp</span> <span class="o">=</span> <span class="n">select_and_clean</span><span class="p">(</span><span class="n">lfp</span><span class="p">)</span>
+    <span class="n">snls</span> <span class="o">=</span> <span class="n">signaltonoise</span><span class="p">(</span><span class="n">clean_lfp</span><span class="p">)</span>
+    <span class="n">best_channel</span> <span class="o">=</span> <span class="n">np</span><span class="o">.</span><span class="n">argmax</span><span class="p">(</span><span class="n">snls</span><span class="p">)</span>
+    <span class="n">snl</span> <span class="o">=</span> <span class="n">snls</span><span class="p">[</span><span class="n">best_channel</span><span class="p">]</span>
+    
+    <span class="n">lim</span> <span class="o">=</span> <span class="n">get_lim</span><span class="p">(</span><span class="n">action_id</span><span class="p">)</span>
+    
+    <span class="n">mask</span> <span class="o">=</span> <span class="n">get_mask</span><span class="p">(</span><span class="n">lfp</span><span class="p">,</span> <span class="n">lim</span><span class="p">)</span>
+    <span class="n">signal</span> <span class="o">=</span> <span class="n">zscore</span><span class="p">(</span><span class="n">clean_lfp</span><span class="p">[</span><span class="n">mask</span><span class="p">,</span> <span class="n">best_channel</span><span class="p">]</span><span class="o">.</span><span class="n">ravel</span><span class="p">())</span>
+    
+    <span class="n">p_xx</span><span class="p">,</span> <span class="n">freq</span> <span class="o">=</span> <span class="n">mlab</span><span class="o">.</span><span class="n">psd</span><span class="p">(</span><span class="n">signal</span><span class="p">,</span> <span class="n">Fs</span><span class="o">=</span><span class="n">lfp</span><span class="o">.</span><span class="n">sampling_rate</span><span class="o">.</span><span class="n">magnitude</span><span class="p">,</span> <span class="n">NFFT</span><span class="o">=</span><span class="n">NFFT</span><span class="p">)</span>
+    <span class="n">psd</span><span class="o">.</span><span class="n">update</span><span class="p">({</span><span class="n">action_group</span><span class="p">:</span> <span class="n">p_xx</span><span class="p">})</span>
+    <span class="n">freqs</span><span class="o">.</span><span class="n">update</span><span class="p">({</span><span class="n">action_group</span><span class="p">:</span> <span class="n">freq</span><span class="p">})</span>
+</pre></div>
+
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+
+</div>
+</div>
+
+</div>
+<div class="cell border-box-sizing code_cell rendered">
+<div class="input">
+<div class="prompt input_prompt">In&nbsp;[18]:</div>
+<div class="inner_cell">
+    <div class="input_area">
+<div class=" highlight hl-ipython3"><pre><span></span><span class="p">(</span><span class="n">psd</span><span class="p">)</span><span class="o">.</span><span class="n">to_feather</span><span class="p">(</span><span class="n">output</span> <span class="o">/</span> <span class="s1">&#39;data&#39;</span> <span class="o">/</span> <span class="s1">&#39;psd.feather&#39;</span><span class="p">)</span>
+<span class="n">freqs</span><span class="o">.</span><span class="n">to_feather</span><span class="p">(</span><span class="n">output</span> <span class="o">/</span> <span class="s1">&#39;data&#39;</span> <span class="o">/</span> <span class="s1">&#39;freqs.feather&#39;</span><span class="p">)</span>
+</pre></div>
+
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+</div>
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+
+<div class="output_wrapper">
+<div class="output">
+
+
+<div class="output_area">
+
+    <div class="prompt"></div>
+
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+<div class="output_subarea output_text output_error">
+<pre>
+<span class="ansi-red-fg">---------------------------------------------------------------------------</span>
+<span class="ansi-red-fg">AttributeError</span>                            Traceback (most recent call last)
+<span class="ansi-green-fg">&lt;ipython-input-18-7660e1d3307d&gt;</span> in <span class="ansi-cyan-fg">&lt;module&gt;</span>
+<span class="ansi-green-fg">----&gt; 1</span><span class="ansi-red-fg"> </span>psd<span class="ansi-blue-fg">.</span>to_feather<span class="ansi-blue-fg">(</span>output <span class="ansi-blue-fg">/</span> <span class="ansi-blue-fg">&#39;data&#39;</span> <span class="ansi-blue-fg">/</span> <span class="ansi-blue-fg">&#39;psd.feather&#39;</span><span class="ansi-blue-fg">)</span>
+<span class="ansi-green-intense-fg ansi-bold">      2</span> freqs<span class="ansi-blue-fg">.</span>to_feather<span class="ansi-blue-fg">(</span>output <span class="ansi-blue-fg">/</span> <span class="ansi-blue-fg">&#39;data&#39;</span> <span class="ansi-blue-fg">/</span> <span class="ansi-blue-fg">&#39;freqs.feather&#39;</span><span class="ansi-blue-fg">)</span>
+
+<span class="ansi-red-fg">AttributeError</span>: &#39;dict&#39; object has no attribute &#39;to_feather&#39;</pre>
+</div>
+</div>
+
 </div>
 </div>
 

actions/stimulus-lfp-response/data/10-calculate-stimulus-lfp-response.ipynb

@@ -19,7 +19,7 @@
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-      "15:15:05 [I] klustakwik KlustaKwik2 version 0.2.6\n"
+      "10:26:07 [I] klustakwik KlustaKwik2 version 0.2.6\n"
      ]
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    ],
@@ -67,7 +67,7 @@
    "outputs": [],
    "source": [
     "output = pathlib.Path('output/stimulus-lfp-response')\n",
-    "(output / 'figures').mkdir(parents=True, exist_ok=True)"
+    "(output / 'data').mkdir(parents=True, exist_ok=True)"
    ]
   },
   {
@@ -104,7 +104,7 @@
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@@ -131,7 +131,7 @@
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@@ -154,7 +154,7 @@
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@@ -168,7 +168,7 @@
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@@ -183,7 +183,7 @@
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@@ -218,7 +218,7 @@
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@@ -230,7 +230,7 @@
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@@ -240,7 +240,7 @@
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@@ -303,13 +303,13 @@
   },
   {
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+   "execution_count": 16,
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        "version_minor": 0
       },
@@ -319,6 +319,13 @@
      },
      "metadata": {},
      "output_type": "display_data"
+    },
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "\n"
+     ]
     }
    ],
    "source": [
@@ -327,6 +334,77 @@
     "    left_index=True, right_index=True)"
    ]
   },
+  {
+   "cell_type": "code",
+   "execution_count": 17,
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "application/vnd.jupyter.widget-view+json": {
+       "model_id": "0184251a265a40a2a1e9910405f05db8",
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+     "output_type": "display_data"
+    },
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "\n"
+     ]
+    }
+   ],
+   "source": [
+    "psd, freqs = {}, {}\n",
+    "for i, row in tqdm(channel_groups.iterrows(), total=len(channel_groups)):\n",
+    "    action_id = row['action']\n",
+    "    channel_group = row['channel_group']\n",
+    "    action_group = f'{action_id}_{channel_group}'\n",
+    "    lfp = data_loader.lfp(action_id, channel_group)\n",
+    "    clean_lfp = select_and_clean(lfp)\n",
+    "    snls = signaltonoise(clean_lfp)\n",
+    "    best_channel = np.argmax(snls)\n",
+    "    snl = snls[best_channel]\n",
+    "    \n",
+    "    lim = get_lim(action_id)\n",
+    "    \n",
+    "    mask = get_mask(lfp, lim)\n",
+    "    signal = zscore(clean_lfp[mask, best_channel].ravel())\n",
+    "    \n",
+    "    p_xx, freq = mlab.psd(signal, Fs=lfp.sampling_rate.magnitude, NFFT=NFFT)\n",
+    "    psd.update({action_group: p_xx})\n",
+    "    freqs.update({action_group: freq})"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 18,
+   "metadata": {},
+   "outputs": [
+    {
+     "ename": "AttributeError",
+     "evalue": "'dict' object has no attribute 'to_feather'",
+     "output_type": "error",
+     "traceback": [
+      "\u001b[0;31m---------------------------------------------------------------------------\u001b[0m",
+      "\u001b[0;31mAttributeError\u001b[0m                            Traceback (most recent call last)",
+      "\u001b[0;32m<ipython-input-18-7660e1d3307d>\u001b[0m in \u001b[0;36m<module>\u001b[0;34m\u001b[0m\n\u001b[0;32m----> 1\u001b[0;31m \u001b[0mpsd\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mto_feather\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0moutput\u001b[0m \u001b[0;34m/\u001b[0m \u001b[0;34m'data'\u001b[0m \u001b[0;34m/\u001b[0m \u001b[0;34m'psd.feather'\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0m\u001b[1;32m      2\u001b[0m \u001b[0mfreqs\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mto_feather\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0moutput\u001b[0m \u001b[0;34m/\u001b[0m \u001b[0;34m'data'\u001b[0m \u001b[0;34m/\u001b[0m \u001b[0;34m'freqs.feather'\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n",
+      "\u001b[0;31mAttributeError\u001b[0m: 'dict' object has no attribute 'to_feather'"
+     ]
+    }
+   ],
+   "source": [
+    "(psd).to_feather(output / 'data' / 'psd.feather')\n",
+    "freqs.to_feather(output / 'data' / 'freqs.feather')"
+   ]
+  },
   {
    "cell_type": "markdown",
    "metadata": {},